SE521679C2 - Method and apparatus for suppressing noise in a communication system - Google Patents

Abstract

A noise suppression system implemented in communication system provides an improved update decision during instances of sudden increase in background noise level. The noise suppression system, inter alia, generates an update by continually monitoring the deviation of spectral energy and forcing an update based on a predetermined threshold criterion. The spectral energy deviation is determined by utilizing an element which has the past values of the power spectral components exponentially weighted. The exponential weighting is a function of the current input energy, which means the higher the input signal energy the longer the exponential window. Conversely, the lower the signal energy the shorter the exponential window. The noise suppression system also inhibits a forced update during periods of continuous, non-stationary input signals (such as "music-on-hold").

Description

As mentioned in the aforementioned U.S. patents, the prior art technique for noise suppression damage occurs when a sudden, sharp increase in the background noise level occurs. known technology, Vilmur a forced update of the noise estimate To overcome the weaknesses in previously mentioned US patents of regardless of whether the voice metric sum of M frames runs without a background noise estimate update, where M in Vilmurs Since one and M an update will occur to- VMSUM patents are recommended be between 50 and 300. frame in Vilmur's patent is 10 milliseconds (ms), assumed to be 100, at least every other second regardless of the sum of the voice metrics, (ie regardless of whether an update is necessary or not).

To impose an update on the noise estimate regardless of the voice metric may result in an attenuation of the user's speech signals regardless of the fact that no additional background noise is added. This in turn results in a deterioration of the sound quality as received by the end user. Furthermore, inputs other than the user's speech signals (for example, “pause music”) can cause problems because the forced update of the noise estimate can occur over continuous intervals.

This is due to the fact that music can span several seconds (or minutes) without sufficient pauses that allow a normal update of the background noise estimate. The prior art will therefore allow a forced update every M-frames as there is no mechanism to distinguish background noise from non-stationary input signals. These invalid forced updates not only attenuate the input signal, but also cause serious interference as the spectral estimate is updated based on a time-varying, non-stationary input signal.

Thus, there is a need for a more precise and reliable noise suppression system for use in communication systems. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 generally depicts a block diagram of a speech encoder for use in a communication system.

Fig. 2 generally depicts a block diagram of a noise suppression system in accordance with the invention.

Fig. 3 generally depicts a frame-to-frame overlap which occurs in the noise suppression system in accordance with the invention.

Fig. 4 generally depicts trapezoidal window handling for pre-stressed samples which occur in the noise suppression system in accordance with the invention.

Fig. 5 generally depicts a block diagram of the spectral deviation estimate depicted in Fig. 2 and used in the noise suppression system in accordance with the present invention.

Fig. 6 generally depicts a flow chart of the steps performed in the update decision determiner depicted in Fig. 2 and used in the noise suppression in accordance with the invention.

Fig. 7 generally depicts a block diagram of a communication system which may advantageously implement the noise suppression system in accordance with the invention.

Fig. 8 generally depicts variables attributable to noise suppression of a tube signal implemented by the prior art.

Fig. 9 generally depicts variables attributable to noise suppression of a voice signal implemented by the noise suppression system in accordance with the invention.

Fig. 10 generally depicts variables attributable to noise suppression of a music signal implemented by the prior art.

Fig. 11 generally depicts noise suppressor variables for a music signal implemented by the noise suppression system in accordance with the invention. lO l5 DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT A noise suppression system implemented in a communication system provides an improved update decision in cases of sudden increase in the background noise level. The noise suppression system, among other things, monitoring deviations for the spectral energy and generating an update by continuously over-enforcing an update based on a predetermined threshold criterion. The spectral energy deviation is determined using an element which has the previous values for the spectral power components exponentially weighted. The exponential weighting is a function of the current input energy, which meant that the higher the input energy, the longer the exponential window. On the contrary, lower signal energy results in shorter exponential windows. This prevents the noise suppression system from forcing an update during periods of continuous, non-stationary input (such as “pause music”).

Generally speaking, a speech encoder implements a noise suppression system in a communication system. The communication system transmits speech samples using frames of information in channels, where the frames of information in the channels have noise therein. The speech encoder has as an input signal speech sample, and a means for suppressing noise based on deviations in the spectral energy between a current frame with a speech sample and a mean spectral energy for a plurality of preceding frames of speech samples for generating noise suppressed speech samples during - the pressing noise in the frame of speech samples. A means for encoding the noise-suppressed speech samples then encodes the noise-suppressed speech samples for transmission of the communication system. In the preferred embodiment, the speech encoder is located either in a centralized base station (CBSC), (MS) for a communication system. However, in alternative embodiments, control unit or a mobile station, the speech encoder may be located in either a mobile switching center (MSC) (BTS). preferred embodiment, or a base receiver station Furthermore, in that the speech encoder is implemented in a (CDMA), it is understood that the speech encoder communication system with code-shared multiple access but one skilled in the art, and the noise suppression system according to the invention have applications for many different types of communication systems.

In the preferred embodiment, the means for suppressing the noise in a frame of speech sample comprises a means for estimating the total channel energy within a current frame for speech sample based on the estimation of the channel energy and a means for estimating the power of spectra for the current frame of speech sample. based on an estimate of the channel energy. Furthermore, a means is included for estimating the power for a spectrum of a plurality of preceding frames of speech samples based on the estimation of the power for the spectra of the current frame.

With this information, a means for determining the deviation between the estimation of the spectrum of the present frame and the estimation of the power of the spectra of the several preceding frames determines a spectral deviation as mentioned, and a means for updating the noise estimate for the channel based on the estimate. of the total channel energy and the determined deviation. Based on the update of the noise estimate, a means for modifying the gain of the channel modifies gain for the channel to generate the noise suppressed speech sample.

In the preferred embodiment, the means for estimating the power of a spectrum of a plurality of preceding frames further comprises means for estimating the power of a spectrum of a plurality of preceding frames based on an exponential weighting of the previous frames of information, wherein the exponential weighting of the previous frames of information is a function of the estimate of the total channel energy 521 679 within a current frame of information. Further in the preferred embodiment, the means for updating the estimated noise for the channel based on the estimate of the total channel energy and the determined deviation further comprise means for updating the estimated noise for the channel based on a comparison of the estimate of the total channel energy with a first threshold value and a comparison of the determined deviation with another threshold value. More specifically, the means for updating the noise estimate for the channel based on a comparison of the estimate of the total channel energy with a first threshold value and a comparison of the determined deviation with a different threshold further comprises means for updating the noise estimate for the channel when the estimation of the total channel energy is greater than the first threshold value for a first predetermined number of frames without a second predetermined number of successive frames having an estimate of the total channel energy less than or equal to the first threshold value, and when the determined deviation is below the second the threshold value. In the preferred embodiment, the first predetermined number of frames is 50 frames while the second predetermined number of consecutive frames is six frames.

Fig. 1 generally depicts a block diagram of a speech encoder 100 for use in a communication system. In the preferred embodiment, the variable rate speech encoder 100 is a variable rate speech encoder 100 suitable for suppressing noise in a code division multiple (CDMA) communication system with Interim Standard (IS) 95. For information on IS-95, see TIA / EIA / IS- 95, "Mobile Station-Base Station Compatibility Standard for Access For More Dual Mode Wideband Spread Spectrum Cellular System", 1993, the embodiment is further the speech encoder with the variable speed July included herein for reference. In the preferred header 100 such that it supports three of the four bit rates allowed by IS-95: full speed ("speed 521 82/79 1" - 170 bit / frame), bit / frame), and 1/8 bit / frame speed). speed ("speed 1/2" - 80 ("speed l / 8 - 16 As one with ordinary knowledge in the field will understand, the embodiment described below is only exemplary; the speech encoder 100 is compatible with many different types of communication systems.

Fig. 1 shows means for encoding noise suppressed speech samples 102 based on the residual code excited (RCELP) algorithm. For more information on the RCELP algorithm, see W.B. Kleijn, P. ”The RCELP Speech- linear prediction which is well known in the art.

Kroon, and D. Nahumi, Coding Algorithm ”, vol 5, For more information on an RCELP algorithm that is European Transactions on Telecommunications, No. 5 September / October 1994, pages 573-582. suitably modified for variable speed operation and for robustness in a CDMA environment, see D. Nahumi and W.B.

“An Improved 8 kb / s RCELP coder”, ICASSP 1995. RCELP is a generalization of the algorithm with code-excited linear prediction (CELP). see B.S. Atal and M.R.

Kleijn, Proc.

For more information on the CELP algorithm, Schroeder, “Stochastic coding of speech at very low bit rates”, Int. 1984, pp. 1610-1613.

Each of the above references is hereby incorporated by Proc. Conf. Comm., Amsterdam, references.

While the above references provide a thorough understanding of the CELP / RCELP algorithms, a brief description of the operation of the RCELP algorithm. Unlike CELP encoders, RCELP does not attempt to match the original user's speech signal exactly. Instead, RCELP matches a "time-distorted" version of the original instruction. the residual which is transformed into a simplified pitch contour by the user's speech signal. The pitch contour of the user's speech signal is obtained by estimating the pitch delay once in each frame, and linearly interpolating the pitch from frame to frame. An advantage of using this simplified pitch representation is that more bits are available in each frame for stochastic excitation and channel attenuation protection than would be the case in traditional fractionated pitch solution. This results in an increased frame error performance without affecting the perceived speech quality in clear channel conditions.

In FIG. 1, the input signal to the speech encoder 100 is a speech signal vector, s (n) 103, and an external speed command signal 106. analog input signal by sampling at a rate of 8000 The speech signal vector 103 may be provided by one sample / sec, and linear (uniform). ) quantizing the resulting speech samples with at least 13 bits of dynamic range. Alternatively, the speech signal vector 103 may be provided by an 8-bit u-layer input signal by converting a uniform pulse coding modulated (PCM) format in accordance with Table 2 of ITU-T Recommendation G.711. the external speed command signal 106 may cause the encoder to generate a blank packet or something other than a speed-1 packet. If an external speed command signal 106 is received, the speed selection mechanism for the speech encoder 100 is received.

The input speech vector 103 is presented for means for suppressing noise 101, which in the preferred embodiment are noise suppression systems 109. The noise suppressing system 109 performs noise suppression in accordance with the invention. A noise suppressing speech vector, s' (n) 112 is then presented for both a speed determination module 115 and a model parameter estimation module 118. activity detection The speed determination module 115 applies a voice (VAD) algorithm and speed output (speed Model parameter selection logic to 1/8, 1/2 or 1) the estimation module 118 performs a linear prediction to be generated. coding (LPG) analysis to generate model parameters 121.

The model parameters include a set of linear (LPCs) model parameter estimation module (LSPs) prediction coefficients and an optimal pitch offset (t). 118 also converts LPC to spectral line pairs and 5231 679 9 calculates long- and short-term prediction gains.

The model parameters 121 are input to a variable rate coding module 124, characterize the excitation signal and quantize the model parameters 121 in a suitable manner for the selected rate. The speed information is obtained from a speed decision signal 139 which is also input to the variable speed coding module 124. If the speed 1/8 is selected, the variable speed coding module 124 will not try to characterize any periodicity in the speed residual, but will instead simply characterize its energy contour. . For speed 1/2 and speed 1, the variable speed coding module 124 will apply the RCELP algorithm to match a time-distorted version of the original user's speech signal residual.

After coding, a packet formatting module 133 accepts all of the parameters calculated and / or quantized in the variable rate coding module 124, and formats a packet 136 suitable for the selected speed.

The formatted packet 136 is then sent to a multiplex sublayer for further processing, as well as the speed decision signal 139. For further details of the overall operation of the speed encoder 100, see IS-127 document "EVRC Draft Standard (IS-127)". 1, No. TR45.5.1.1 / 95.10.17.06, 17 October 1995, herein by reference.

Fig. 2 generally depicts a block diagram of an improved noise suppression system 109 in accordance with the scope of the invention. In the preferred embodiment, the noise suppression system 109 is used to improve the signal quality transmitted to the model parameter estimation module 118 and the speed determination module 115 for the speech encoder 100. However, the operation of the noise suppression system 109 is generic to the extent that it is capable of operating at any type of speed encoder that a design engineer may wish to implement in a CF RJ ... à O \ \ J \ O specific communication system. It is noted that several blocks depicted in Fig. 2 of the present application have a similar operation to the corresponding blocks depicted in Fig. 1 of U.S. Patent Application No. 4,811,404 to Vilmur. Thus, U.S. Patent Application No. 4,811,404 to Vilmur, with the same applicant as to the present application, is incorporated herein by reference.

The noise suppression system 109 includes a high pass filter (HPF) 200 and a residual noise suppression circuit. The output signal from HPF 200 & m (n) is used as the input signal to the remaining noise suppressor circuit. Although the frame size of the speed encoder is the frame size is 20 ms (as defined by IS-95), for the remaining noise suppressing circuit 10 ms. As a result, in the preferred embodiment, the steps of performing noise suppression in accordance with the invention are performed twice with a 20 ms speech frame.

To start noise suppression in accordance with the invention, the input signal s (n) (HPF) HPF 200 is the fourth order Chebyshev type II of the high pass filter 200 to generate the signal am (n). with a cut-off frequency of 120 Hz, which is well known in the art. The transfer equation for HPF 200 is defined as: where the respective follower and denominator coefficients are defined to be: b = {0.898025036, -3.59010601, 5.38416243, -3.59010601, 0.898024917, a = {1.0 , -3,78284979, 5,37379122, -3,39733505, 0,806448996} gp I * .J .¿ O \ »J QS 11 As one of ordinary skill in the art will appreciate, any number of high pass filter configurations may be used.

Then, in the pre-stressed block 203, the window & w (n) is windowed using a smoothing in which the first D-samples d (m) are overlapped from the last D-trapezoidal windows, by the input frame (frame "m") The sample for the previous frame (frame "m-1"). This overlap is best seen in FIG. 3. Unless otherwise noted, all variables have initial values of zero, for example, d (m) = 0; ms O. This can is described as: d (m, n) = d (m - 1, L + n); O sn <D, where m is the current frame, n is the sample index of the buffer {d (m)}, L = 80 is the frame length, and D = 24 is the overlap (or delay) in the samples, the remaining samples for the input buffer are then precast in accordance with the following: d (m), D + n) = Shp (n) + §pShp (n - 1 ); 0 sn <L, where CP = 0.8 is the pre-emphasis factor, resulting in the input buffer containing L + D = 104 samples in which the first D samples are the pre-stressed overlap from the previous frame, and the following L the samples are fed from inside current frame.

Next, in the window handling block 204 of FIG. 2, a smoothing trapezoidal window 400 (FIG. 4) is applied to the samples to form a discrete Fourier transform In the preferred embodiment for (DFT) input signal g (n). g (n) is defined as: a (m, n) sin2 (ny) + os) / 2D): 0 sn <D.) _ dwm); D $ nm "'a (m, n) sin2 (» ( n-L + D + os) / 2D); Lsn Q; D + Lsn 679 12 where M = 128 is the DFT sequence length and all other terms are defined as before.

In the channel divider 206 in FIG. 2, to the frequency domain using the (DFT) defined as: the transformation of g (n) is performed discrete Fourier transform M-1 G (k) = å2gnp "j27 fl k / M; (M, Mn = 0 where e fl teaches a unit amplitude complex phase with an instantaneous radial position w. This is an atypical definition, but one that exploits the efficiency of the complex fast Fourier transform (FFT) .The 2 / M scale factor comes from pre-processing the M-point real sequence to form a M / 2-point complex sequence which is transformed using an M / 2-point complex FFT In the preferred embodiment 65 channels. Details other, include the signal G (k) if this technique can be found in Proakis and Manolakis, Introduction to Digital Signal Processing, 2nd edition, 1988, pages 271-722. then input to New York, Macmillan, Signal G (k) the channel energy estimator 109 where the channel energy estimate Ew (m) for the current frame, m, is determined using the following : IuÜ) E ,,, (m, f) = max Em,, a ,,, (m) s ,,, (m -1, i) + (1-a ,, (m)) Xpoqf; k = gm OSi 0.0625 is the minimum allowable channel energy, aw (m) (defined below), NC = 16 is the number of combined channels, and fL (i) and fH (i) are the izte element for the respective low and high channel combination tables , fL and f fl. Preferably, fL and f fl are defined as: where Emin = is the equalization factor of the channel energy design, gr í \ 3 .é Q \ 1 \ O 13 {2,4,6,8,10,12, 14, 17,20,23, 27.3l, 36,42,49,561, Ü n f fl = 3,5,7,9, ll, 13,16, 19,22,26,30,35,4l, 48,55,63).

The channel energy equalization factor, am (m) 0; m s 1, Gm (m) = m> l. Assumes a value of zero for the 0.45; which means that am (m) (m = 1) and a value of 0.45 for all subsequent frames. the estimate is initialized for the unfiltered channel- In addition, the channel first frame This allows the channel energy energy for the first frame. the noise energy estimate (as defined below) is initialized for the channel energy of the first frame, i.e.: En (m, i) = max {Eim¿, Ecnhn, i)}; m = 1.0 s in <NC, where Enut = 16 is the minimum allowable channel noise initialization energy.

The channel energy estimate Em (m) for the current frame is then used to estimate the signal-to-noise ratio (SNR) index of the quantized channel. estimation is performed in the channel SNR estimator 218 in FIG. 2, Den fl a and is determined as: oq (i) = max {0, min (89, round {1 Ologw OLWSHJ; 0 si <NC, where En (m) is the current channel noise energy estimate (as defined later), and the values of {oq} are limited to be between 0 and 89, including the same.

Using the channel SNR estimate {oq}, the sum of the voice metrics in the voice metric calculator 215 is determined using: can be defined as: also input to a total channel energy estimator 503, 14 N -1 y (m) = i = 0 where V (k) is the kzte the value of 90 elements of the voice metric table V, which is defined as: V = {2,2,2,2,2,2,2,2,2,2,3,3,3,3,3,4,4,4 , 4,5,5,5,6,6,7,7,7,8,8,9, 9,10,10,11,12,12,13,13, 14,15,15,16,17 , 17,18, 19,20,20,21,22,23, 24,24,25,26,27,28,28,29,30,3l, 32,33,34,35,36,37,37 , 38,39,40,41, 42,43,44,45,46,47,48,49,50,50,5o, 50,50,50,5o, 5o, 50,5o}.

The channel energy timer Ew (m) for the current frame is also used as an input to the spectral deviation estimator 210, which estimates the spectral deviation AE (m). Referring to FIG. FIG, the channel energy estimator Em (m) is input to a low power spectral estimator 500, where the low power spectrum is estimated as: EdB (mrj -) = log10 (Ech (mri)); 0 5 <NC- Channel energy timer Em (m) for the current frame to determine the total energy estimate EtM (m) for the current frame, m, according to the following: N -1 Elvf (m) = 1o 'OQ1O {E Enn (m 1: 0 Next, an exponential window handling factor, a (m) (as a function of the total channel energy Etm (m)) is determined in the exponential window handling factor 506 using: g (m) = a ”- J (EH - EWÜTÛ ), which is limited between an and QL by: Mm) = max MIL, minw fl, <1 (m>}}, where EH and EL are the energy endpoints (in decibels or lldB / l) transformed into a (m) for the linear interpolation of EUm (m), which which has the limits aL s ag.

The values of these constants are defined as: EH = 50, EL =, an = 0.99, QL = 0.50. with a relative energy of, nential window factor of d (m) Given these, a signal 40 dB would use an expo- = 0.745 using the above calculations, said calculations.

The spectral deviation Aghn) is estimated in the spectral deviation estimator 509. The spectral deviation AE (m) is the difference between the current power spectrum and a mean value of the long-term power spectral estimate: N _ A5 (ff7) § ä1lída (m, í) - gds (m, i) l, I = 0 where Éæ (m) is the mean of the long-term spectral power estimate, which is determined in the long-term spectral energy estimator 512 using: šßgün + l, i) = Q (m) EdBün, i ) + (1G (m)) EdBUn, i); Os i <NC, l0 (TI J M 679 16 where all variables are previously defined. The initial value of E fi (m) is defined to the estimated log power spectrum for frame 1, or: šdß = Edwm, -m = 1.

At this point, the sum from the voice metrics is entered into the total channel energy estimate of the presence- to the updated decision determiner 212 to facilitate Decision v (m), the frame EUn (m) and the spectral deviation AEUM noise suppression in accordance with the invention. the logic, shown below in pseudo-code and depicted in the form of the flow chart in FIG. 6, demonstrates how noise estimation update decisions are finally performed. The process starts at step 600 and continues to step 603, where the update flag (update_flag) is reset. Then, at step 604, the update logic (VMSUM only) for the voice metric v (m) is implemented by Vilmur by checking whether the sum is less than an update threshold value (UPDATE_THLD). If the sum of the voice metrics is less than the update threshold value, the update counter 605 is reset, for steps 603-606 is shown below: (update_cnt) at step and the update flag is set at 606. Pseudocode update_flag = FALSE: if (v (m) s UPDATE_THLD) {update_THLD) {update_ update_cnt = 0 If the sum of the voice metrics is greater than the update threshold at step 604, noise suppression is implemented in accordance with the invention. First, at 607, the total channel energy estimate, for the current frame, m, is compared with the noise floor in dB Et @ t (HÜ I (NOISE_FLOOR_DB) while the spectral deviation AE (m) is compared with the deviation threshold value (DEV_THLD). å 17 the total channel energy estimate is greater than the noise floor and the spectral deviation is less than the deviation threshold value, the update counter is increased at step 608.

After the update counter is incremented, a test is performed at step 609 to determine if the update counter is greater than or equal to an update threshold (UPDATE_CNT_THLD). If the result of the test at step 609 is true, step 606. below: then an update flag is attached to the Pseudo-code for steps 607-609 and 606 is otherwise displayed if ((EUm (m) update_cnt = update_cnt + 1 if (update_cnt 2 UPDATE: CNT_THLD) update_flag = TRUE As can be seen from FIG. 6,> NOISE_FLOOR_DB) and (AEUn) are implemented if any of the tests at steps 607 and 609 are false, or after the update flag has been set at step 606, logic to prevent long-term "creep" This hysteresis logic is implemented to prevent minimal spectral deviations from accumulating over long periods of time, causing an incorrectly imposed update.The process starts at step 610 where a test is performed to determine whether the update counter has been equal to the last update counter value for the last six frames (HYSTER_CNT_THLD) In the preferred embodiment (last_update_cnt) six frames are used as the threshold value, but any number of frames can be implemented. If the test at step 610 is true, the update counter is reset at step 611, and the process proceeds to the next frame at step 612. If the test at step 610 is false, at step 612. the process goes directly to the next frame Pseudo-code for the steps 610-612 is shown below: if (update_cn == last_update_cnt) hyster_cnt = hyster_cnt + 1 ânnâIS LU L fl tr wa ._å c \ \ J WD 18 0 update_cnt hyster cnt last_update_cnt if (hyster_cnt> HYSTER_CNT_THLD) update_c.

In the preferred embodiment, the values of the previously used constants are used as follows: UPDATE_THLD = 35, NOISE_FLOOR_DB = 1010gm (1), DEv_THLD = 28, UPDATE_cNT_THLD HYsTER_cNT_THLD 50, and Whenever the update flag is set for the next frame frame, in accordance with the invention. The channel noise timer is updated in the smoothing filter 224 using: En (m + lri) z maX {Emin / anEn (m / i) + (l_an) Ech (m / i)}; 0 5 <NC where Emm = 0.0625 is the minimum allowable channel energy and an = 0.9 is the channel noise equalization factor stored locally in the equalization filter 224. The updated channel noise estimator is stored in the energy estimate memory 225, the updated channel noise estimate is En (m). and the output signal from the energy estimation memory 225. The updated channel noise estimate One (m) is used as an input signal to the channel SNR estimator 218 as described above, and also to the gain calculator 233 as will be described below.

Thereafter, the noise suppression system 109 determines whether a channel SNR modification is to occur. This determination is performed in the channel SNR modifier 227, which counts the number of channels which have channel SNR index values which exceed an index threshold value. During the modification process itself, the channel SNR modifier 227 SNR is reduced for those specific channels that have an SNR index U ro -à G \ »J \ o 19 less than an adversity threshold value (SETBACK_THLD), or reduces the SNR for all channels by the sum for the voice metric is less than a metric threshold (METRIC_THLD). A pseudocode representation of the channel SNR modification process occurring in the channel SNR modifier 227 is provided below: index-cnt = 0 for (i = NM to NC - 1 step 1) {if (Oq (i) 2 INDEX-THLD) index_cnt = index_cnt + 1} if (index_cnt <INDEX_CNT-THLD) TRUE modify_flag then modify_flag FALSE if (modify_flag == TRUE) for (i = 0 to NC - 1 step 1) SMETRIC-THLD) (Oq (i) sSETBACK_THLD)) o “q (i) = 1 if ((v (m) or else Ü \ q (i) = Üq (i> annaIS {Ü \ q} = {0q} At this point, the channel's SNR index {oq '} is limited to an SNR threshold value in the SNR threshold block 230.

The constant is stored locally in the SNR threshold block 230. A pseudo-code representation of the process performed in the SNR threshold block 230 is provided below: for (i = 0 to NC - 1 step 1) If (Ü \ q (i) <ÜÜÜ O ” q (i) = 0th 5221 6379 fl nn H vn QUAAAQLL-J In the preferred embodiment, the previous constants and thresholds are set to: NM = 5, INDEXJHLD 12, INDEX_CNT_THLD = 5, METRIC_THLD = 45, SETBACK_THLD = 12, = 6. and At this point, the limited SNR indices {øq ”} are input to the gain calculator 233, where the total gain is determined by the channel.First, the factor of use using: N -1 1 '. Y” = max { ym, n, -1Olog, 0 (-: - 2 E ,, (m, /)]}, EIIOOI, ^ = ° where WMR = -13 is the total minimum gain, it is estimated I that Ymin and Efloor E fl if = 1 is the noise floor energy, and One (m) noise spectrum calculated under the previous frame. Preferred embodiment, the constants are stored locally in the gain calculator 233. Thereafter, the channel gain (in dB) is determined by an inversion of: Ya fl i) = ug (O "q (i) - Om) + Yn; 0 S i <NC, where ug = 0.39 is the gain slope (also stored locally in the gain calculator 233). The linear channel gains are then converted using öVZ rch (f) = mi fl10 '““' ”°}; o sf <NC. 521 63 "? 21 At this point, the channel gains determined above for the transformed input signal G (k) are applied with the following criterion to generate the output signal H (k) from the channel gain modifier 239:: whisper fH BHHBTS H (k) = { 7cn (i fi (k) G (k) š The other condition in the above equation assumes that the interval for k is O s M / 2. It is further assumed that H (k) is also symmetric, so that the following condition is also introduced: H ( M - k) = H (k); O <k <M / 2. To the time domain of the signal H (k) the channel combiner 242 is converted (back) using the inverse DFT: 1 M4 'zum / M h,: _ Hqpl ; 0sn (mn) 2 and the frequency domain filtering process is completed to generate the output signal h '(n) by applying overlap and addition with the following criterion: h_ (n) _ h (m, n) + h (m-1, n + L); 0 sn <ML. _ hmmm; M-Lsn Signal emphasis (“deemphasis”) is applied to the signal h '(n) by means of the tone block 245 to generate the signal s' (n) which has been noise suppressed in accordance with invented ningen: s' (n) = h '(n) + §ds' (n-1); O s n <L, where šd = 0.8, the decoupling factor is stored locally within the deconstruction block 245. Fig. 7 generally depicts a block diagram of a communication system 700 which may advantageously implement the noise suppression system in accordance with the invention. In the preferred embodiment, the communication system is a cellular radiotelephone system (CDMA). In the field will be understood, However, as one of ordinary knowledge, the noise suppression system according to the invention shared multiple access can be implemented in each communication system which can benefit from the system. It is important to note, limited to, voice messaging systems, telephone systems, interurban communication systems, planar communication systems, etc. that the noise suppression system in accordance with the invention may be advantageously implemented in combination systems which do not include speech coding, for example analog cellular radiotelephone systems.

In FIG. 7, abbreviations are used for convenience. The following is a list of definitions for abbreviations used in FIG 7: BTS Base receiver station CBSC Centralized base station controller EC Echo extinguisher VLR Visitor location register HLR Home location register ISDN Service integrated digital network MS Mobile station MSC Mobile connection center MM Mobility operations center and Mobility operations center switchboard PSTN Publicly connected telephone network TC Converter As shown in Fig. 7, a BTS 701-703 is connected to a CBSC 704. Each BTS 701-703 provides radio frequency (RF) communication to an MS 705-706. In the preferred embodiment, the transmitter / receiver (transceiver) hardware implemented in BTS 701-703 and MS 705-706 is defined to support RF communication in the document entitled TIA / EIA / IS-95, " Mobile Station-Base Station Compatibility Standard for Dual Mode Wideband July 1993, available through the Telecommunication Industry Association (TIA). CBSC Spread Spectrum Cellular System, 704 is responsible for the call process via TC 710 and mobility management via MM 709. In the preferred embodiment, the functions of the speech encoder 100 are shown in FIG. 2 in TC 704. Other tasks for CBSC 704 include function control and transmission. / network adaptation. For more information on the functions of CBSC 704, reference is made to U.S. Patent Application No. 07 / 997,997 to Bach et al., With the same assignee as the present application, which is incorporated herein by reference.

Furthermore, Fig. 7 depicts an OMCR 712 connected to MM 709 for CBSC 704. the general maintenance of the radio part CBSC 704 and BTS 701-703) CBSC 704 is connected to an MSC 715 which provides switching possibilities between PSTN 720 / ISDN 722 and CBSC 704. OMCS 724 is responsible for the operation and general maintenance of the switching part (MSC 715) HLR 716 and VLR 717 provide communication system 700 with user information- OMCR 7123 is responsible for the operation and (communication of the communication system 700. of the communication system 700. mation primarily used for advertising purposes EC 711 and 719 are implemented to improve the quality of the speech signal transmitted through the communication system 700.

The function of CBSC 704, MSC 715, CPR 716 and VLR 717 is shown in FIG. 7 as distributed, however, one of ordinary skill in the art may understand that the function may likewise be centralized to a single element.

Furthermore, TC 710 is likewise arranged at either MSC 715 or a BTS 701-703.

Since the function of the noise suppression system can for different configurations, 109 is generic, the present invention relates to the implementation of noise suppression according to the invention in one (for example MSC 715) (for example CBSC 704). element while the speech coding function In this embodiment, the noise suppressed signal s '(n) is transmitted in another element (or data representing the noise suppressed signal s' (n)) from MSC 715 to CBSC 704 via link 726.

In the preferred embodiment, the TC 710 performs noise suppression in accordance with the invention using the noise suppression system 109 shown in FIG. 2. The link 726 interconnecting the MSC 715 via the CBSC 704 is a T1 / E1 link which is well known in the art. By placing the TC 710 at the CBSC, a 4: 1 improvement in the link budget is achieved due to the compression of the input (input from the T1 / E1 link 726) of the TC 710. compressed the signal transmitted to a specific BTS 701-703 for transmission to and specific MS 705-706. The signal It is important to note that the compressed signal is transmitted to a specific BTS 701-703 undergoes further processing at BTS 701-703 before transmission. In other words, the possible signal transmitted to MS 705-706 is different in form but the same in substance as the compressed signal leaving TC 710. leaving TC 710 has undergone a noise suppression in accordance In each case, the compressed signal as with the invention using of the noise suppression system 109 (shown in FIG. 2).

When MS 705-706 receives the signal transmitted by BTS 701-, MS 705-706 will essentially "restore" all processing performed by BTS 701-703 and the speech coding performed by TC 710. When MS 705-706 sends a signal back to BTS 701-703, MS 705-706 also implements speech coding. Thus, the speech encoder 100 in FIG. 1 is also found in MS 705-703, (usually referred to as "decoding"). 706, and thereby noise suppression in accordance with the invention is also performed by MS 705-706. After a signal which has undergone noise suppression is transmitted by MS 705-706 (MS also performs further processing of the signal for 521 679 to change the shape, but not the substance, of the signal) to a BTS 701-703, BTS 701-703 will " "reset" the processing performed on the signal and transmit the resulting signal to the TC 710 for speech decoding. After the speech decoding of TC 710, the signal is transmitted to an end user via the T1 / E1 link 726. Since both the end user and the user in MS 705-706 finally receive a signal which has undergone noise suppression in accordance with the invention, each user is capable to enjoy the benefits provided by the noise suppression system 109 in the speech encoder 100.

Fig. 8 generally depicts noise suppressing variables of a voice signal implemented by the prior art, while Fig. 9 generally depicts noise suppressing variables of a voice signal as implemented by the noise suppressing system in accordance with the invention. Here the different groups show values of different state variables as one as shown on the horizontal (graph 1) Fig. 9 shows the total channel energy EU fi (m), function of the frame number, m, the axis. The first graph in each of FIG. 8 and followed by the voice metric sum v (m), the update counter (update_cnt or TIMER in Vilmur), the sum of the channel noise estimates the update flag (EENUM / I)) I estimated the signal attenuation 10logw (Enmm / Eompm), where it (update_flag ), and the input signal is Sw (n) and the output signal is s' (n).

As seen in FIG. 8 and FIG. 9, basic noise is observed in graph 1 just before frame 600. the increase in background signal. Before frame 600, the input signal was a "pure" (low background noise) voice signal 801. When a sudden increase in background noise 803 occurs, depicted in graph 2 proportionally therewith and the previously known increase the voice metric sum v (m) the noise suppression method is substandard. The possibility of recovery from this relationship is shown in graph 3, allowed to increase as the update counter (update_cnt) as long as no update is performed. This 26 example shows that the update counter reaches the update threshold value (UPDATE_CNT_THLD) of 300 (for Vilmur) during active speech at around frame 900. At approximate frame 900, the update flag (update_flag) is set as shown in graph 4, resulting in a background estimate update. using the active speech signal as shown in graph 5. This can be observed as an attenuation of the active speech as shown in graph 6. It is important to note that the update of noise estimation occurs during the speech signal (frame 900 in graph 1 is during speech), with the effect that the speech signal is “forced” when an update was unnecessary. Furthermore, since the threshold of the update counter decreases to expire during normal speech, a relatively high threshold (300) is required in an attempt to prevent such an update.

Referring to FIG. 9, the update counter is incremented only during background noise increase, but before the speech signal begins. This allows the update threshold to be lowered to a value of 50, which still maintains a reliable update. Here, the update count (UPDATE_cNT ~ THLD) of 50 at frame 650, which gives the noise suppressor near the update counter threshold 109, sufficient time to adjust to the new noise conditions before returning to the speech signal at frame 800. During this time it can be seen that the attenuation occurs. only under non-speech frames in which no “coercion” of speech signals occurs. The result is an improved speech signal as heard by the end user.

The improved speech signal is due to the fact that the update decision is made based on key deviations between the current frame energy and an average of the previous frame energy, instead of simply letting a timeout expire in the absence of normal voice metric updates. In the latter case (like Vilmur), does the system see the sudden increase in noise as a speech signal in itself, and is thus not capable of distinguishing the increased background noise level from a 521 6? 27 true speech signal. Using spectral deviations, the background noise can be distinguished from the true speech signal, and an improved update decision is consequently made.

Fig. 10 generally depicts noise-suppressing variables for a music signal as implemented by the prior art, while Fig. 11 generally depicts noise-suppressing variables for a music signal as implemented by the noise-suppressing system in accordance with the invention. ningen. For exemplary reasons, 600 in Fig. 10 and Fig. 8 and Fig. 9. the prior art method in much the same way as back- At frame 600, the music signal 805 renders a substantially continuous voice - the signal up to frame 11 is the same pure signal 800 shown appears in Fig. Referring to Fig. 10, the basic noise example depicted in Fig. 8. the geometry sum v (m) as shown in graph 2 which is finally "run over" by the update counter (see graph 3) at frame 900. As the characteristic of the music signal 805 changes over time, the attenuation shown in graph 6 decreases, but the update counter continuously runs over the voice metric shown at frame 1800. In contrast, as best seen in Fig. 11, the update counter (as seen in graph (UPDATE_CNT_THLD)) of 50 and thus no update occurs.The fact that no 3) never a threshold value update occurs can most easily be understood with reference to graph 6 in Fig. 805 is a constant 0 dB Thus, 11, where the attenuation of the music signal (i.e. no d mpning occurs). a user listening to the music (e.g. a "pause music") which is noise suppressed with prior art will hear unwanted changes in the music level while a user listening to music which is noise suppressed in accordance with the present invention will hear music at the desired art - take the level.

While the invention has been specifically shown and described with reference to a specific embodiment, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and purpose of the invention. the invention. The corresponding structures, materials, activities and equivalents for all organs or steps plus functional elements in the claims below are intended to include any structure, material, or activity to perform the function in combination with other elements mentioned in the claims as specified.

Claims (33)

10 l5 20 25 30 521 679 vi ». . ». 1 PATENT REQUIREMENTS A method for suppressing noise in a communication system, the communication system performing information transmission using frames with information in channels, the frames with information in channels having noise resulting in a noise estimation for the channel, the method comprising the steps to: estimate a channel energy within a current frame with speech sample; estimating a total channel energy within a current frame with speech sample based on the estimation of the channel energy; estimating an effect of a spectrum for the current frame with speech samples based on the estimation of the channel energy; estimating an effect for a spectrum of a plurality of previous frames with speech samples based on the estimation of the effect of the spectra of the current frame; determining a deviation between the estimated spectrum of the current frame and the estimated power of the spectrum of the several previous frames; and updating the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation. The method of claim 1, further comprising the steps of modifying a gain for the channel based on the update of the noise estimation to generate a noise suppressed signal. The method of claim 1, wherein the steps of estimating an effect for a spectra of a plurality of previous frames further comprise the steps of estimating an effect of a spectra of a plurality of previous frames based on an exponential Weighing of the previous frames. 70670 requirements l April 2003.doc lO 15 20 25 30 521 679 Jê. .. A method according to claim 3, wherein the exponential weighting of the previous frames is a function of the estimation of the total channel energy within a current frame with speech sample. The method of claim 1, wherein the steps of updating the noise estimation for the channel based on the estimation of the total channel energy and determining the deviation further comprise the step of updating the noise estimation for the channel based on a comparison of the estimation of the total channel energy with a first threshold value and a comparison of the determined deviation with a second threshold value. The method of claim 5, wherein the steps of updating the noise estimation for the channel based on a comparison of the estimation of the total channel energy with a first threshold value and a comparison of the determined deviation with a second threshold value further comprise the step of updating the noise estimation for the channel when the estimation of the total channel energy is greater than the first threshold value and when the determined deviation is below the second threshold value. The method of claim 6, wherein the step of updating the noise estimation for the channel when the estimation of the total channel energy is greater than the first threshold value and when the determined deviation is below the second threshold further comprises the step of updating the noise estimation for the channel when estimating of the total channel energy is greater than the first threshold value for a first predetermined number of frames without a second predetermined number of consecutive frames having an estimate of the total channel energy less than or equal to the first threshold value. 70670 claim l April 2003.doc lO 15 20 25 30 521 6779 3! «. <- @ -. A method according to claim 7, wherein the first predetermined number of frames comprises 50 frames. A method according to claim 7, wherein the second predetermined number of consecutive frames comprises six Iâ fl üir. A method according to claim 1, wherein the method is performed in either a mobile switching center (MSC), a centralized base station controller (CBSC), a base receiving station (BTS) or a mobile station (MS). 11. ll. Device in a communication system, wherein the communication system performs information transmission using frames with information in channels, where the frames with information in the channels have noise which results in a noise estimation of the channel, where the apparatus comprises; means for estimating the channel energy within a current frame with speech sample; means for estimating a total channel energy within a current frame with speech samples based on the estimation of the channel energy; means for estimating an effect for a spectrum of the present frame with speech samples based on the estimation of the total channel energy; means for estimating an effect for a spectrum of a plurality of previous frames with speech samples; means for determining the deviation between the estimation of the spectra of the current frame and the estimation of the effect of the spectra of the several previous frames; and means for updating the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation. 70670 claim April 1, 2003.doc 10 15 20 25 30 The apparatus of claim 11, further comprising means for modifying a gain for the channel based on the update of the noise estimation to generate a noise suppressed signal. Device according to claim 11, wherein the device is connected to a speech encoder which has the noise-suppressed signal as input signal. The device according to claim 11, wherein the device is located in either a mobile switching center (MSC), a centralized base station controller (CBSC), a base receiving station (BTS) or a mobile station (MS) of a communication system. The device of claim 14, wherein the communication system further comprises a code division multiple access (CDMA) communication system. The apparatus of claim 11, wherein the means for estimating the power of spectra of a plurality of previous frames with speech samples further comprises means of estimating the power of a spectrum of a plurality of previous frames based on exponential weighting of the previous frames with speech sample. The device according to claim 16, wherein the exponential weighting of the previous frames with speech sample is a function of the estimation of the total channel energy within a current frame with speech sample. 70670 claim April 1, 2003.doc 10 15 20 25 30 521 67 33 The apparatus according to claim 11, wherein the means for updating the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation further comprises means for updating the noise estimation for the channel based on a comparison of the estimation of the total the channel energy with a first threshold value and a comparison of the determined deviation with a second threshold value. The apparatus of claim 18, wherein the means for updating the noise estimation for the channel based on a comparison of the estimation of the total channel energy with a first threshold value and a comparison of the determined deviation with a second threshold value further comprises means for updating the channel. dating the noise estimation for the channel when the estimation of the total channel energy is greater than the first threshold value and when the determined deviation is below the second threshold value. The apparatus of claim 19, wherein the means for updating the noise estimation for the channel when the estimation of the total channel energy is greater than the first threshold value and when the determined deviation is below the second threshold value further comprises means for updating the noise path. - the increase for the channel when the estimation of the total channel energy is greater than the first threshold value for the first predetermined number of frames without the second predetermined number of consecutive frames having an estimate of the total channel energy which is less than or equal to the first the threshold value. The device of claim 20, wherein the first predetermined number of frames comprises 50 frames. 70670 claim l April 2003.doc 10 15 20 25 30 5221 679 37 A device according to claim 20, wherein the second predetermined number of consecutive frames comprises six Ia flfl ír. A speech encoder for speech coding in a communication system, the communication system transmitting speech samples using frames with information in channels, the frames with information in channels having noise therein, the speech encoder having a speech sample as input signal, and wherein the speech encoder comprises: means for suppressing noise in a frame with speech sample based on a deviation in the spectral energy between an existing frame with speech sample and a mean spectral energy for a plurality of previous frames with speech sample for generating noise-suppressed speech samples; and means for encoding the noise suppressed speech samples for transmitting the communication system. A speech encoder according to claim 23, wherein the speech encoder is located in either a mobile switching center (MSC), a centralized base station controller (CBSC), a base receiving station (BTS) or a mobile station (MS) for a communication system. The speech encoder of claim 24, wherein the communication system further comprises a code division multiple access (CDMA) communication system. A speech encoder according to claim 23, wherein means for suppressing the noise in a frame with speech sample further comprises: means for estimating the total channel energy within an existing frame with speech sample based on the estimation of the channel energy; 7067O requirement 1 April 2003.doc 10 15 20 25 30 ('VX ro ¿G \ \ 2 \ O 3§ means for estimating the power of a spectrum for the current frame of speech sample based on the estimation of the channel energy; means for estimating the power of a spectrum for a plurality of previous frames of speech samples based on the estimation of the power of the spectra of the current frame; and means for updating the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation, and means for modifying a gain for the channel based on updating the noise estimation to generate the noise suppressed speech samples. A speech encoder for encoding speech in a communication system, the communication system transmitting speech signals using frames of information in channels, the frames of information in channels having noise therein, the speech encoder having as input signal a speech signal, wherein the speech encoder comprises: means for suppressing noise in a frame comprising the speech signal based on a deviation in the spectral energy between an existing frame comprising the speech signal and a mean spectral energy for a plurality of previous frames including speech signals for generating noise suppressed speech signals; and means for encoding the noise suppressed speech signals for transmitting the communication system. A speech encoder according to claim 27, wherein the speech encoder is located in either a mobile switching center (MSC), a centralized base station controller (CBSC), a base receiver station 70670 claim 1 April 2003.doc 10 l5 20 25 30 (BTS) or a mobile station (MS) for a communication system. The speech encoder of claim 28, wherein the communication system further comprises a code division multiple access (CDMA) communication system. The speech encoder according to claim 27, wherein the means for suppressing noise in a frame comprising the speech signal further comprises: means for estimating the total channel energy within a present frame comprising the speech signal based on the estimation of the channel energy; means for estimating the power of a spectrum of the present frame comprising the speech signal based on the estimation of the channel energy; means for estimating the power of a spectrum for a plurality of previous frames comprising speech signals based on the estimation of the power of the spectra of the current frame; means for determining a deviation between the estimation of the spectra of the current frame and the estimation of the power of the spectra of the several previous frames; and means for updating the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation; and means for modifying the gain of the channel based on the update of the noise estimation to generate the noise suppressed speech signal. A speech encoder according to claim 30, wherein the speech signal is either an analog speech signal or a digital speech signal. 70670 requirements l April 2003.doc 10 15 20 25 30 521 6Éï ~ f9 sr A method in a communication system, wherein the communication system performs information transmission using frames with information in channels, wherein the frames with information in channels have noise which results in a noise estimation for the channel, the method comprising the steps of: estimating a channel energy within a current frame with speech sample; estimating a total channel energy within a current frame with speech sample based on the estimation of the channel energy; estimating an effect of a spectrum for the current frame with speech samples based on the estimation of the channel energy; estimating an effect for a spectrum of a plurality of previous frames with speech samples; determine a deviation between the estimated spectrum of the current frame and the estimated power of the spectrum of the several previous frames; and updating the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation. A method in a communication system, wherein the communication system performs information transmission using frames with information in channels, wherein the frames with information in channels have noise which results in a noise estimation for the channel, the method comprising the steps of: estimating a channel energy within a current frame with speech sample; estimating a total channel energy within a current frame with speech sample based on the estimation of the channel energy; estimating an effect of a spectrum for the current frame with speech samples based on the estimation of the channel energy; estimating a first power for a spectrum of a plurality of previous frames with speech samples not based on the estimation of the power of the spectra of the current frame; 70670 requirement 1 April 2003.doc (H ha .AO \ \ 5 2? Estimate a second power for a spectrum of a plurality of previous frames with speech samples based on the estimation of the power of the spectra for the current frame; determine a deviation between the estimated spectrum for the current frame and the estimated first power for the spectrum for the several previous frames, and update the noise estimation for the channel based on the estimation of the total channel energy and the determined deviation.